Product Data for Fragrances: Structuring Scent Families and Sizes

Two bottles sit next to each other on the shelf: same brand, same 100 ml, same box design. One is an Eau de Toilette, the other an Eau de Parfum — different concentration, a different note pyramid, a different price. To a customer who can't tell them apart, your shop is broken. The difference lives entirely in the product data, and if that data is buried in a free-text description, no filter, no comparison and no scent-family search will ever surface it.

Product data for fragrances is attribute data: scent family, top/heart/base notes, concentration and fill size are the fields that make a fragrance findable and comparable. Everything else — the marketing prose, the hero image — is secondary. This is a focused sub-topic of beauty and cosmetics retail, where fragrance is the most attribute-driven category of all.

Why is fragrance data so attribute-heavy?

Most product categories have a handful of specs. A fragrance has a structured profile that customers actively shop by:

• Scent family: floral, woody, oriental, fresh, chypre, fougère — the primary way people browse. Without it, no scent-family filter.
• Note pyramid: top, heart and base notes. Often written as prose in supplier data, it needs to become three structured fields to power note search.
• Concentration: Eau de Cologne, Eau de Toilette, Eau de Parfum, Parfum/Extrait — the single attribute most often confused when it lives in the title instead of a field.
• Fill size & format: 30 / 50 / 100 ml, plus refill, travel spray and gift set — the variant axis of the whole category.

Do this by hand across dozens of suppliers and it doesn't scale. The fix is the same as everywhere: consolidate, normalize, enrich and publish — but for fragrance, the normalize step is where the value concentrates.

Don't the brand feeds and the rest cover it?

For the marquee houses, the brand feeds do a lot of the work. The big listed lines often arrive with clean master data, images and even a structured note pyramid. That covers the branded core everyone stocks.

The problem is everything outside those feeds:

• Niche and indie houses that ship a PDF with the note pyramid written as a sentence.
• Private-label and drugstore ranges where you are the data source.
• Seasonal and gift-set SKUs that land as a supplier Excel weeks before the season.
• Older or discontinued lines whose data was never cleanly captured anywhere.

So the real setup is two-track: clean brand feeds for the marquee core, and manual spreadsheet-and-PDF work for the long tail. The feeds solved the easy part; the painful attribute extraction on the niche is still done by hand.

Which attributes and standards structure a fragrance — and where do they stop?

There is no single dominant fragrance-specific data standard the way TecDoc governs car parts. What you have instead is a set of attribute conventions plus the general retail identifiers. Here's what carries the load and where each layer stops:

In short: GTIN/EAN and the brand feeds give you identity and the branded core, but they rarely give you filterable scent families, structured notes and clean concentration across the whole assortment. That gap — turning prose into structured attribute groups — is the real work.

How does Productbay structure fragrance data?

The throughline is a three-step job — and it's exactly what Productbay is built for:

• Consolidate: import every source once — brand feed, supplier CSV, Excel, PDF datasheet, feed URL, FTP, API — and match by GTIN/EAN so a 50 ml and a 100 ml of the same scent become clean size variants instead of two unrelated products.
• Structure & enrich: model reusable attribute groups — scent family, top/heart/base notes, concentration, size/format — and let AI read those values out of titles and PDF descriptions, write sales copy, assign categories and translate via DeepL, always with a review queue before anything publishes.
• Publish: two-way sync to Shopify and Shopware, ERP connections (Xentral, weclapp) and feed exports for Amazon, OTTO and Kaufland — each with per-channel transformations.

Crucially, Productbay starts where the brand feeds end. If the marquee houses already feed your core, great — Productbay complements them, structures the attribute groups the feeds never carried cleanly, and takes over the niche longtail no standard provides for. Productbay is built for specialist retailers running multi-supplier, multi-channel catalogs — from mid-sized shops to large chains.

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